Connecting audiences with climate change: Towards humanised and

action-focused data interactions

Marta Ferreira

, Nuno Nunes , Pedro Ferreira , Henrique Pereira , Valentina Nisi

I.S. T

ecnico, Universidade de Lisboa, Lisboa, Portugal

ARTICLE INFO

Keywords:

Data humanism

Data visualization

Communication

Climate Change

HCI

ABSTRACT

This paper investigates the relationship between design research and humancomputer interaction (HCI) in the

context of climate change communication and engagement. We discuss current practices in climate change

communication and the decrease in concern and engagement caused by “crisis fatigue”. Through Research

through Design (RtD), we set out to investigate data humanism and how users react to climate change data,

testing approaches to improve engagement. With this purpose, we designed and evaluated Finding Arcadia, an

interactive data story that uses data humanism to shift the dialogue from crisis-focused to action-focused. One

study with the original IMF visualisations (N = 17) and two studies in public spaces (N = 12 and N = 64) point to

the contextualization of the data and presenting actionable solutions helping in engaging users with climate

change issues; help in creating solution-focused narratives and interpreting and relating with climate data. From

these results, we derive insights for designing empowering interactive data visualizations for resilient climate

change engagement.

1. Introduction

Climate change is one of the most signicant challenges we face

today. Communicating about climate change is fundamental to mobi-

lizing action, countering misinformation, and conveying a helpful

message that empowers and motivates people to engage. Just recently,

the UN recognized the importance of communicating climate change by

establishing guidelines (U. N. D. of Global Communications 2022) cen-

tred on three main areas: i) use authoritative scientic information; ii)

convey the problem and the solutions; and iii) mobilize action. These

guidelines reinforce the importance of positive engagement, storytell-

ing, personalization, and presenting solutions to work towards

empowerment and counter “crisis fatigue” – when prolonged exposure

to unexpected and stressful events leads to burnout (Coelho, 2020).

Climate change is an increasing concern in Human-Computer Inter-

action (HCI) and design research (Ferreira et al., 2021; Mencarini et al.,

2023; Williams et al., 2022; Doggett et al., 2023). Sustainable HCI

(SHCI), in particular, focuses on enhancing human well-being while

minimizing environmental impacts (DiSalvo et al., 2010). One initial

approach was to argue for SHCI research to articulate clear or design

specic sustainability goals and metrics on a project-by-project basis

(Silberman et al., 2014). Later, Knowles et al. asserted that we could

better pursue cohesion by establishing a sound understanding of sus-

tainability that could bring the community together (Knowles et al.,

2018). One of the takeaways was that we should orient HCI work around

climate change rather than the more broadly multidimensional concept

of “sustainability”. The rationale stems from Klein’s premise that climate

change provides a much-needed coalescing narrative that does not

distract us from the existential urgency (Klein, 2015).

However, there is increasing evidence of “crisis fatigue” – a phe-

nomenon where people become overwhelmed and desensitized by re-

petitive exposure to negative events and related emotional framings,

which leads to decreased concern and public engagement (Beehler,

2019; Flinders, 2020; Bloodhart et al., 2019; Feinberg et al., 2011;

O’Neill and Nicholson-Cole, 2009). Hence, an increasing number of

studies point to the need for communication strategies that don’t focus

only on negative framing, but consider action and feelings of efcacy

(Hart and Feldman, 2016; Doherty and Webler, 2016; Feinberg et al.,

2011; Corner et al., 2018), personalization and emotional connections

(Gustafson et al., 2020), adaptation to diverse audiences (Chapman

et al., 2017) and create a sense of hope and possibility (Ojala, 2012;

Ojala, 2022; Stern, 2012).

In this article, we argue for the potential of data humanism to provide

a general framework for prioritizing the ethical and human values in the

* Corresponding author.

E-mail address: amartaferreira@tecnico.ulisboa.pt (M. Ferreira).

Contents lists available at ScienceDirect

International Journal of Human - Computer Studies

journal homepage: www.elsevier.com/locate/ijhcs

https://doi.org/10.1016/j.ijhcs.2024.103341

Received 25 August 2023; Received in revised form 17 July 2024; Accepted 17 July 2024

Int. J. Human–Computer Studies 192 (2024) 103341

Available online 30 July 2024

design and interpretation of climate change data(24). Data humanism,

proposed by information designer Giorgia Lupi in a manifesto (G. Lupi,

2017), is a philosophy in data processing and visualization that priori-

tizes human needs and values, advocating for individualized and

nuanced perspectives while emphasizing context and personal experi-

ence over traditional infographics. Following this approach, data should

be communicated alongside storytelling and relatable metrics that give

meaning and context to the numbers. We propose that this design

approach can be used to make the science of climate change accessible

and engaging to a broad audience, aligning with UN’s guidelines:

“Presenting data alone may numb the audience. Make it relatable, local, and

personal ” (U. N. D. of Global Communications 2022).

We contribute to climate change communication in HCI by pre-

senting Research through Design (RtD) (Zimmerman et al., 2010) proj-

ect that explores how data humanism can engage audiences with climate

change data in a personalized, contextualized, and action-focused way.

Our project takes the form of an interactive data-story (Fig. 1) that

communicates ocean-related data based on International Monetary

Fund (IMF) research (Chami et al., 2019). The study evaluates how this

visualization approach can foster positive and empowering interactions

with climate change data. To achieve this, we focus on three research

questions: a) If and how users feel connected to the humanized data; b) If

the humanized data affords users a positive outlook on climate change;

c) If solutions-oriented visualizations create a feeling of empowerment

and agency towards climate matters. Moreover, we discuss the results

from the application of the novel Data Humanism design approach

(Ferreira et al., 2023), and derive implications for future HCI and design

research in climate change communication.

The rest of the paper is organised as follows: rst, we present the

related work around communication and engagement with climate

change topics. Secondly, we present the design and implementation of

the Finding Arcadia project, which is based on data humanism principles.

Thirdly, we report on the studies performed. The study’s results high-

light how users are aware and concerned with climate change, how their

behavior can make a difference, but also how governing institutions play

an important role. Regarding the data humanism strategies, results show

that the storytelling strategy helped in giving meaning to the data “ab-

stract” numbers. Moreover, the unfamiliar topic (whales as a carbon-

capturing solution) effectively engaged users. Finally, linking the story

to action was seen as useful but was not sufcient to signicantly shift

the established negative framing associated with climate change.

We conclude by discussing future directions, pointing to the need to

add context to climate change data, how the solutions-oriented data-

story helped in giving users a sense of agency, and simultaneously, the

challenge of countering the negative framing associated with climate

change. This discussion led to insights for future work in HCI and Design

for action-focused interactions with climate change data.

2. Related work

This research builds on prior work in climate change communication

and SHCI. In the following, we summarise i) recent discussions and

proposals regarding climate change communication and how the HCI

and design research communities have been addressing this topic, ii)

HCI projects that embrace a data humanism approach, and iii) Recent

HCI approaches connecting users with data.

2.1. Interacting with climate change data

2.1.1. Climate change communication and engagement

Communicating climate change is highly complex. The scale of the

problem, which demands widespread citizen participation and systemic

change (IPCC 2018; Wuebbles et al., 2017), means that a multitude of

data needs to be conveyed, together with the urgency of the problem and

the underlying science. The impact of this data depends on how the

information is imparted. The debate around climate change message

framing is ongoing, and studies on the efcacy of different communi-

cation strategies have returned mixed results. Some studies point to

fear-inducing messages causing stronger reactions when compared to

hope (Hornsey and Fielding, 2016) while other studies report inducing

fear not having a signicant effect on climate change risks perception

(Ettinger et al., 2021). Other scholars highlight that the simple refram-

ing of the message (e.g. changing the discourse on sustainability efforts

from their benets for climate change mitigation to other types of

benets such as innovation, health benets, or community building) is

unlikely to increase public support (Bernauer and McGrath, 2016). On

the other hand, evidence demonstrates that fear is ineffective in moti-

vating personal engagement with climate topics, but it can attract peo-

ple’s attention (O’Neill and Nicholson-Cole, 2009). Another study calls

attention to people’s preference for messages framed without emotion,

rather than through negative emotions (Bloodhart et al., 2019). For

(Feinberg et al., 2011; Hart and Feldman, 2016; Doherty and Webler,

2016), solution-oriented messages seem to assist in the perception of

efcacy and engagement, pointing to the importance of linking

communication to action (Doherty and Webler, 2016). A positive frame

reinforces public support (Dasandi et al., 2022) and hope appeals can be a

powerful tool to be harnessed in persuasive communication (Chadwick,

2015). On a similar note, guidelines for climate change communication

have pointed to the importance of framing the interaction positively to

avoid a “feeling of hopelessness” (Corner et al., 2015), as a narrow

narrative focusing exclusively on “doom and gloom” leaves the public

feeling powerless (Arnold, 2018). Reporting the impacts of climate

change exclusively portrays an incomplete view of society. Stories about

constructive problem-solving, for example, are often neglected. Climate

change must be presented as solvable (Mayer and Smith, 2019), shifting

the focus from assumed sacrices to what becomes possible (Tonkin-

wise, 2011). Data needs to be presented in a relatable way, using stories

besides graphs and statistics to connect it to what matters to that

Fig. 1. Two screens of the data-story with captions of the data humanism aspects explored, and the installation in the science museum (pilot study).

M. Ferreira et al.

International Journal of Human - Computer Studies 192 (2024) 103341

audience, including solutions in the narrative (Chapman et al., 2016;

Corner et al., 2018). Personal stories can be a persuasive communication

strategy to engage diverse and even sceptical audiences (Gustafson et al.,

2020). A wider selection of narratives is needed (O’Neill et al., 2015).

Because of its complexity and potentially polarising nature, climate

change interactions cannot depend on single, universal engagement

strategies. (Chapman et al., 2017) suggests an audience-focused

approach based on message tailoring, focusing on the individual’s

particular needs and avoiding a “one-sizets-all” approach. HCI has

already explored strategies to support more complex forms of commu-

nication. Moving forward, we must operationalize methods in adapt-

able, engaging, and structured approaches for climate change-related

interactions.

2.1.2. Interactions with climate change in HCI and design research

A recent survey based on the past decade of HCI and design research

concluded that most interaction design projects provide a neutral mes-

sage, i.e., they communicate through a neutral framing based on ex-

amples and data visualizations, with no suggestions for action (Ferreira

et al., 2022). This is consistent with mainstream media’s “pragmatic”

data communication strategy. This study points to the opportunity of

choosing less explored and less-known topics, including more inclusive

perspectives such as i) taking the communication activities to

daily-routine places and therefore engaging users “where they are”; ii)

proposing actionable steps as part of the interaction, supporting positive

framing and feelings of agency; and iii) adapt the message to the

particular audience you are engaging with. While addressing this

research, we followed these guidelines to promote inclusive and

action-focused climate change interactions.

Climate change is a fast-growing topic in the HCI community, and

the communication and interaction strategies employed are diverse.

Applied research has looked into leveraging the impact of emotions and

a sense of community to communicate climate change topics (Arag´on

et al., 2021). Besides engaging local communities in critical discourse, it

successfully links to action through connecting to local organizations

and services (Paraschivoiu and Layer-Wagner, 2021). Through this

research, the authors engaged with the importance of playful and

location-based experiences, recognizing how long-term engagement is

challenging, especially with people who are not interested in sustain-

ability (Paraschivoiu and Layer-Wagner, 2021). In the home context,

environmental awareness related to users’ behavior has been tested

through a data sculpture (Stegers et al., 2022), highlighting the impor-

tance of personal and group data for deeper understanding and the

challenges of communicating complex information. Still, there was no

concrete information on the impact of the sculpture on users’ further

actions or reections on the climate change topic.

The importance of how environmental data is sorted and framed

(highlighting certain attributes of items) has been shown to affect

energy-saving decisions (Starke et al., 2021). Another inuencing factor

is personalization, which can lead to enhanced data engagement

through familiarity (Van Den Bosch et al., 2022).

These projects demonstrate the plethora of strategies focused on

climate change action, relation to the community, or how the data is

presented to a particular audience, highlighting a timely and rich arena

for investigation. However, to our knowledge, no other research project

has combined HCI with a focus on positive framing, data humanism, and

climate change data engagement, furthering Ferreira et al. (Ferreira

et al., 2022) guidelines and implications. Our study focuses on the ef-

cacy of such communication strategies in informing future HCI climate

change communication work.

2.2. Data humanism

2.2.1. Data visualisation and a shift towards humanisation

There is little agreement on the best way to visualize complex data

for lay audiences (Meloncon and Warner, 2017). Leading authors on

data visualization from the past three decades have greatly focused on

the efciency of design and clarity of communication in what can be

categorized as a “neutrality” principle (Zhao and Sun, 2022). Tufte

proposed a distraction-free approach focused mainly on presenting the

actual data and avoiding chartjunk (Tufte, 2013). Others have pointed to

the importance of accuracy and clarity for effective and efcient

communication (Few, 2012) and warn against the persuasive misuse of

data visualizations (Cairo, 2016) or suggest following applied human

perception (Ware, 2021). This leads to the storytelling approach sum-

marized by McCandless: information (data), story (concept), goal

(function), and visual form (metaphor) (McCandless, 2014). Storytelling

gains greater relevance in data visualization design, marking a shift from

neutral to humanistic representations. It also embraces ambiguity and

complexity, contrasting the claims of information being value-neutral or

observer-independent (Drucker, 2011). In 2016, Lupi proposed a para-

digm shift in how we represent data, moving away from impersonality

and questioning “truth” and simplicity principles. Named data human-

ism, the approach encourages the audience to slow down, explore,

engage with, and appreciate the visualization (Richards, 2022). Lupi has

formalized this call in a manifesto that encourages information de-

signers to: 1) Embrace complexity – move away from the need to keep

visualizations as simple as possible, allowing for layered communica-

tion; 2) Move beyond standards – create customised designs for the spe-

cic data being worked; 3) Sneak context in – consider subjectivity and

context; and 4) Remember that data is imperfect – data is ”human-made”

and, therefore, does not represent a ”universal truth”; research and

translation can help in understanding (G. Lupi, 2017). The purpose is to

create engaging and personalized data-driven visual narratives that link

the numbers to what they stand for – stories, knowledge, people, and

behaviors (G. Lupi, 2017; Lupi, 2018) – by adding qualitative informa-

tion that supports contextualisation and meaning. This method opens

opportunities for designers to be more creative and look beyond the

standard chart types, inspiring alternative human-data interactions.

There is an emphasis on user participation, leading to an emotional

experience that relates to humanistic qualitative information, not just

quantitative (Zhao and Sun, 2022). Emotion is crucial in building

memories and making meaningful decisions (Immordino-Yang and

Damasio, 2007). Strategies that allow appraisal of information in

rational but also emotional ways are essential (Canossa et al., 2022).

Data humanism uses data as a tool that allows for reality to be

imagined and understood, as data is a partial and subjective represen-

tation of reality, dependent on how it is collected and selected (Ippoliti

et al., 2020). Visual depictions facilitate the interaction between in-

dividuals and their social and political realities (Piron and Paraguai,

2019). Zhao and Sun (Zhao and Sun, 2022) discussed recent aesthetic

strategies in information visualization with a signicant focus on

“humanising” data. They point towards “conceptual speculation” to

move beyond the established “empirical induction” by: a) embracing

emotional experiences – emphasising emotional aspects of the data to

trigger reection; b) using visual metaphorical rhetoric – the importance

of metaphors to highlight points of view; c) that speculative design cata-

lyzes social dreams – stimulate thinking about dreams and values that can

lead to changes in behavior. For example, data representations that raise

awareness for sustainable behaviors on university premises have used

comparisons of distances to make the vast numbers more comprehen-

sible, in line with data humanism principles (Ceccarini et al., 2023).

Making data contextual and intimate (G. Lupi, 2017), and therefore

“reconnected to our lives and our behaviors” (Lupi, 2018), align with

recent communication guidelines for climate engagement: “Presenting

data alone may numb the audience. Make it relatable, local, and personal”

(U. N. D. of Global Communications 2022); and with Meloncon and

Warner’s (Meloncon and Warner, 2017) opportunities for future work

derived from their literature review on data visualisations: an emphasis

on contextualisation and context awareness, and allowing users to select

more personalised data to display through the use of interactive dis-

plays. Therefore, data humanism’s conceptual and formal strategies

M. Ferreira et al.

International Journal of Human - Computer Studies 192 (2024) 103341

present a promising response to the challenges in climate change

communication discussed in 2.1.1.

2.2.2. Data humanism in HCI research

Data humanism comes into HCI research as one of the most recent

contemporary perspectives on data visualization, enabling a shift of data

ownership towards people, embedding data in everyday experiences

(Ferreira et al., 2023).

Data humanism, in particular, the Dear Data project (Lupi et al.,

2016), has inspired researchers to test its blend of data exploration and

hands-on approach to assist in data literacy (Byrd, 2021; Krekhov et al.,

2019) broadening users’ notion of what data could be and the multitude

of ways it can be visualised. “Data seles” are now standard (e.g. in

dating or exercise apps), representing oneself through data, and can lead

to self-reection and discussion (Robards et al., 2021). Data humanism

arguably takes these self-expressions one step further. Two studies

inspired by Dear Data focus on personalization by creating custom vi-

suals (Kim et al., 2019; Romat et al., 2020), leading to deeper engage-

ment and enjoyment. Nevertheless, these representations face the

challenge of balancing readability and aesthetics. The possibility of

creating more complex and unusual data visualizations necessarily re-

quires more availability from users. The design of impactful,

metaphor-based visualizations can educate and communicate several

layers of information simultaneously (Angulo et al., 2020).

Humanising strategies were used to propose a hybrid data approach

that enhances the meaning of quantitative urban IoT data, by adding

layers of context-specic qualitative data (Houben et al., 2019). Simi-

larly, a layered design that combined ”abstract and numerical” feedback

about daily behavior raised environmental awareness and facilitated

reection (Sauv´e and Houben, 2022).

Research points to the potential of data humanism to support deeper

data connections and data understanding through diverse, playful and

enjoyable explorations (Kim et al., 2019; Krekhov et al., 2019). These

projects highlight the importance of connecting lay audiences with data

through less “neutral” and more engaging approaches, countering

research’s typical focus on limited visualization types (Meloncon and

Warner, 2017). The HCI community has been debating its role in

building more sustainable futures, including in “making data under-

standable, usable, and actionable” (Mencarini et al., 2023). However, to

our knowledge, no other HCI research has tested data humanism in

climate changerelated visualizations. Building on previous work, we set

out to understand if data humanism – focused on personalization, con-

textualization, and connecting to action – fosters positive and empow-

ering interactions with climate change data.

2.3. HCI approaches connecting users with data

Engaging users with data in “new ways” is not a novelty in HCI

research, and some approaches share methods or intentions with data

humanism. Storytelling has long been used in data representation to

enhance visual expression and assist in conveying meaning (Rodr´ıguez

et al., 2015). Using strategic interactive elements along the story for user

exploration of the data has been mentioned as an effective strategy for

engagement (Segel and Heer, 2010). This interactivity can add contex-

tual, “humanising” layers to the data. Regarding environmental data,

eco-feedback experiences are a popular method of materialising energy

and other sustainability-related data, especially in the home (Barreto

et al., 2014; Pereira and Nunes, 2020) or community (Bird and Rogers,

2010) settings. These projects have a personalization component that

responds directly to user behavior. Also related to sustainability, pro-

jects such as the Indoor Weather Stations (Gaver et al., 2013) or Energy

Babble (Gaver et al., 2015) have worked towards the physicalization of

environmental data. When exploring how the users engage with the data,

data physicalization (Jansen et al., 2015), sometimes called physical

visualisations (Jansen et al., 2013), helps people to explore and under-

stand data through physical representations (Hogan and Hornecker,

2012). Similarly, tangible user interfaces (TUI) allow users to interact

with digital information through physical artefacts (Holmquist et al.,

2019; Ullmer and Ishii, 2000). Like data humanism, data physicalisation

and TUIs explore alternative data presentation formats that frequently

demand more user attention but can also lead to deeper engagement.

These strategies can engage larger audiences with complex data, espe-

cially in public spaces (Hornecker and Buur, 2006), as people tend to

spend time and effort exploring the experience (Jansen et al., 2015; Bae

et al., 2022). Likewise, these approaches to data can be highly subjective

because of the need to select and translate data into these physical forms

(Waldschu¨tz and Hornecker, 2020). Still, they can help elicit affective

responses, reection, and memorability.

Another strategy that can be conceptually linked to data humanism is

adding context to the data and enhancing relatability through connec-

tion to location. “Situatedness of use” has been explored by bringing

outside data inside the home (Gaver et al., 2008), while

location-awareness was used to relate users with “big data” about the

areas they are in (Gaver et al., 2016). These approaches are examples

within HCI that work towards connecting users to somewhat abstract or

complex data, bringing it to everyday settings.

Data humanism shares characteristics with these established HCI

elds. However, we argue this approach can contribute to new venues

within HCI data visualisations, especially within complex and polarising

topics like climate change. Data humanism avoids over-simplication

and focuses on aesthetics, exploration, storytelling, and a deep

connection to emotional and personal value. It can be leveraged in

developing more inclusive perspectives – not only in “humanising”

complex data, mainly related to sustainability but also in creating

meaningful non-anthropocentric connections (Akama et al., 2020; For-

lano, 2017; Light et al., 2017) within complex data sets.

3. Research prototype: nding arcadia

Derived from the challenge of engaging users with more accessible

and actionable data visualizations, the research reported in this paper

sets out to understand: a) If and how users feel connected to the hu-

manized data; b) If the humanized data affords users a positive outlook

on climate change; c) If solutions-oriented visualizations create a feeling

of empowerment and agency towards climate matters. To address these

research questions, we started by summarising data humanism princi-

ples (G. Lupi, 2017) into a formalised design approach (Ferreira et al.,

2023). This paper contributes to the rst studies of the Data Humanism

design approach.

3.1. Development approach and design decisions

The research prototype was developed following RtD (Zimmerman

et al., 2010). First is the Grounding stage. We discussed related work and

performed a systematic review of projects (Ferreira et al., 2022),

pointing to the importance of focusing the message on action, taking the

interactions to “where the audience is”, engaging audiences with less

explored and exploited topics, and presenting alternative and more in-

clusive perspectives – including the perspective of other species and the

importance of cohabitation (Kobayashi, 2014; Smith et al., 2017; Man-

cini and Lehtonen, 2018; Light et al., 2017). Our design decisions

worked to address these gaps, and looked at “a broader suite of solu-

tions” (Wilkinson, 2020), including natural sinks (land, coastal and

ocean). In this direction, a recent International Monetary Fund (IMF)

report (Chami et al., 2019) describing whales as one natural solution for

climate change mitigation – i.e. each great whale sequesters 33 tons of

CO2 on average (Chami et al., 2019). This study had great coverage in

mainstream media (e.g. (Stone, 2019; Yeo, 2021; Randow, 2019)) and

was accompanied by visualisations, presenting an opportunity for visual

analysis.

The following stages in RtD are Ideation and Iteration. During the

ideation stage, the authors debated possible media outputs,

M. Ferreira et al.

International Journal of Human - Computer Studies 192 (2024) 103341

implementation locations, stories and character journeys. We settled on

an interactive data humanism story installation to bring the data to

diverse audiences in a public location. Therefore, through ve design

steps (Section 3.2) we designed the data-story centred around a main

character, Baltazar, the Blue Whale (3.2 – DH.2).

After completing the rst story draft, we conducted four online co-

design sessions with entertainment and HCI experts to rene the

narrative and a session with a marine biologist to validate the scientic

data. In these sessions, the rst author presented the data-story through

the sketched storyboards and narrated the audio content that would be

used for each section of the story. She would then take notes on the

suggestions presented by the experts. Changes from these sessions

include rening the whale data used (e.g. being mindful of the lack of

scientic consensus on some aspects of the biology and behavior of

marine mammals), changes to the story structure to include a tighter and

more dramatic plot, changes to the user input strategy (having input

elds next to each visualisation instead of asking all the information in

the beginning of the experience). The nal version of the prototype

underwent further validation through a pilot study described in Section

4.1.3. The nal iteration of the study was used in the main study,

described in Section 4.2 of this article.

3.2. Prototype overview and applying data humanism

Data humanism proposes connecting the data to qualitative infor-

mation, allowing for contextualization and personalization. This

approach hopefully makes the data more relevant to users. To oper-

ationalise data humanism, we derived ve steps from Lupi’s propositions

(G. Lupi, 2017; Lupi, 2018) and proposed a novel Data Humanism

design approach (Ferreira et al., 2023).

In the following, we summarise the main design decisions related to

the ve steps derived from the data humanism approach (Fig. 2 and 3). A

detailed description of the design decisions can be found in (Ferreira

et al., 2023).

• DH.1. Frame the question that triggered the data exploration: our

focus is on communicating oceans as crucial for global climate

through the ocean carbon cycle data (Chami et al., 2019), and whales

as a fundamental part of the ecosystem (Johnson et al., 2022), as well

as connecting the data to people’s lives.

• DH.2. Discover what is unique about the data: We strived to create

empathy through the whale story, highlighting cohabitation and

lessknown natural solutions. The ocean and whale CO2 cycle data,

along with other environmental data, is communicated through the

original story of Baltazar, the Blue Whale (Fig. 2 and 3), and his

adventures as he navigates the oceans in search of Arcadia, a special

place his mum took him as a child. Along the way, he explains the

CO2 cycle and also confronts the consequences of the Anthropocene,

such as plastic pollution, the consequences of whaling, or shipping

density.

• DH.3. Dene the story to communicate through the data: We crafted

a positive but accurate story centred around the whale life cycle.

Attention was focused on the positive framing of the climate change

topic, e.g., showing the dramatic numbers caused by decades of

commercial whaling while calling attention to the slow but expo-

nential rise after the international whaling ban (Fig. 2-1). We also

communicated resilience and hope by ending the character’s journey

naturally, and this was not caused by the dangers he faced (Fig. 3-6).

Another crucial aspect was closely connecting to action throughout

the story, underpinning the idea of “hope” and giving a sense of

agency. We proposed solutions related to each section’s topic (Fig. 3-

5) – e.g., related to plastic pollution: “Look for natural bres” or “Buy

veggies and fruit not wrapped in plastic”; related to ship density:

“Buy local products” or “If you do tourism in the sea, make sure it’s

with a certied company”; or linking to CO2 emission reduction:

“Reduce food waste” or “Buy less stuff”.

• DH.4. Provide meaning and context to the audience: Throughout

the story, data was contextualised to assist in interpretation. The data

was communicated through the story of one particular (humanised)

whale, connecting the data to sections of Baltazar’s life. Further-

more, the climate change data is accompanied by layers of “quali-

tative data” (comparisons to more familiar metrics and situations),

including actionable solutions. Examples of this are the carbon cycle

and whale carbon/oxygen ux, where we add additional information

or compare the data with more approachable information – CO2

absorbed by phytoplankton compared with trees, with CO2 emitted

by countries the user can choose from, adding elements for size

comparison, etc. (Fig. 2-3).

• DH.5. Humanise the data: We conceptualised strategies that allowed

for personal customization of the visualisations. To help the audience

relate to the data, we enriched the visualizations with personal layers

of information from the user’s input, adapting to, for example, their

date of birth, height, or country (Fig. 2-2). We also added climate

change information related to the Tagus River (Fig. 3-4), as this

community has a profound social and historical connection to sh-

ing, navigation, tide milling, and other river activities.

4. User study

This section describes the goals and measures used in the prototype

testing and explains the context and protocol used to examine the

research questions. Finally, we detail the data analysis and results.

Our study process included a baseline study with the original IMF

data visualizations and two “in the wild” studies with our interactive

data-story (Fig. 4). We set up the interactive story to be experienced

through a touchscreen display, where users could interact directly with

the data visualizations (Fig. 5). The screen was placed in a triangular

module made of recycled plastic – one face supported the screen and two

other faces where equipped with tangible elements that users could

engage with and leave their feedback on – one face allowed users to

leave feedback about the story by answering two questions with col-

oured dot stickers, and the other face encouraged users to leave mes-

sages through post-its (Fig. 5b).

Since the installation was placed in public locations and the purpose

of the study was to engage diverse publics through the chosen contexts

of implementation, there was no previous recruitment of participants.

Passersby were casually approached for participation. Before replying to

the anonymous questionnaire (no personal data was collected), partic-

ipants received an overview of the study, emphasizing that the evalua-

tion focused on the artefact rather than on them personally, that they

could withdraw at any time, and could ask any questions to the

researcher. The participants of the follow-up interviews were asked to

sign a consent form containing the study information, along with the

researcher’s contact details, as this part of the study was not conducted

in a public context. This study involved only adult participants (over

eighteen years old) with no specic population focus. Apart from age,

there were no other disqualifying criteria.

4.1. Pilot experimental study

During the ve-day UN Ocean Conference, we conducted the pilot

study in a major science museum in the city of Lisbon. The pilot was

meant to test the data-story, understand its appeal to various audiences,

and pilot the interview protocol.

4.1.1. Methods

The installation was placed inside the museum in an area accessible

only to conference visitors and then moved to a passage location for two

days accessible to all visitors (Fig. 5-a). Three researchers (the rst,

third, and fourth authors) were involved in the study. All three took

turns noting observations and engaging with users to conduct the user

interview.

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International Journal of Human - Computer Studies 192 (2024) 103341

Fig. 2. Sequence of screenshots from the interactive visualizations that summarise Baltazar’s story, complete with the data humanization: (U. N. D. of Global

Communications 2022) Give a positive spin to the narrative; (Coelho, 2020) Allow the user to personalize the visualization; (Ferreira et al., 2021) Contextualise the

data by comparing and adding layers of “soft” (qualitative) data.

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International Journal of Human - Computer Studies 192 (2024) 103341

Fig. 3. Sequence of screenshots from the interactive visualizations that summarise Baltazar’s story, complete with the data humanization: (Mencarini et al., 2023)

Make the data relatable to this particular community; (Williams et al., 2022) Focus on action by proposing solutions; (Doggett et al., 2023) Design the character

journey as resilient.

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During the ve days of implementation, observations were noted

regarding the user’s stance, attitude, and comments towards the

installation in general, and the data-story interactions in particular. The

researchers observed at a distance and allowed users to start the activity

alone. After the interaction, the researcher approached users, explained

the purpose of the study, and asked if they could answer a brief anon-

ymous interview based on four demographic questions and six open

questions, which included: “Before this experience, did you associate

climate change with the oceans? And with whales?”; “What did you

think of the way the information was presented?”; “Do you think the

information presented is relevant to your life?”; “How did the story

make you feel?”; “Did the story inspire you to take action? How?”. We

gathered twelve user interviews (P1 to P12).

4.1.2. Participants

To understand better how adults deal with the negative communi-

cation around climate change and crisis fatigue we focused our study on

adults (over 18 years old) – young adults (aged 18-34): n=3; adults

(aged 35-64): n=7; senior adults (aged 65-74): n=2. Regarding gender,

n=7 identied as women and n=5 as men. All twelve users were

educated at the undergraduate level or higher.

4.1.3. Results of the pilot study

From the results of the pilot study, the prototype was rened. The

main improvements are described below:

• Longer sections of the story without interactive elements (only with

visuals and narration) made users disengaged. The interactive fea-

tures (e.g., buttons, sliders, and clickable components) promoted

engagement and understandability of the data: “It helped to under-

stand. (…) The interactive elements helped to contextualize. It’s not so

dense.” (P12).

• Some users thought the information was helpful for them and for

society in general. Some commented that the solutions proposed

were not actions they could do themselves, hence disconnected from

their everyday lives (e.g., related to public policy): “The solutions

specic to the oceans are not so actionable. Other things like the ships, you

can only ask for government action.” (P7); “I can’t have much impact in

these matters.” (P10);

• Participants highlighted that proposals for action provided a more

positive framing of climate change. However, some positive data (e.

g., the whale population numbers rising) and the perceived negative

and overwhelming general topic of climate change provided a

certain cognitive dissonance: “Happy to know whale numbers are

recovering.” (P1); “More the perspective of the future, trying to help.

Focus more on action than on the negative.” (P5); “I felt a bit defeated

because I feel there isn’t much I can do but felt good because I saw some

things are getting better. Like the increase in whale numbers.” (P7); “It

added information. It was nice seeing the whale numbers going up. That’s

a positive thing. The info about ships and the noise depresses me because I

don’t see a quick solution.” (P9).

Fig. 4. Scheme of the different study phases and their purpose within the overall research.

Fig. 5. Deployment of the prototype: (a)(b) Pilot study in the science museum; (c) Main study in the local food market.

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4.1.4. Renement of the prototype for main study

The outcomes of the pilot led to several revisions in the prototype:

• The story was shortened to make the experience more concise;

• More interactive components were added to the visualizations,

allowing further personalization and humanization of the data;

• Some of the proposed solutions were rened to better appeal to the

audience that wanted to be able to act upon them, and

• We rened the evaluation protocol, adopting an evaluation survey

based on a Likert scale and further open questionnaire, for more

varied data sets and a more straightforward approach in the wild.

The audience engaged in the pilot study also informed the placement

of the main study, as we wanted to reach a more diverse group of users.

4.2. Main experimental study

We decided to implement the main study in a local food market in the

city of Lisbon to cater to a more diverse population of non-experts. As

Emily Dawson has shown, low-income and less formally educated

groups experience exclusion from spaces of informal science education,

such as science museums, often considering that those spaces “are not

for them” (Dawson, 2014). A truly socially transversal engagement

practice with climate change data must consider these challenges.

Furthermore, we would be engrossed in a local community, taking

climate change data to a place users attend in their routine while capi-

talizing on the novelty of such an activity in that context. The physical

installation maintained the same structure as in the pilot study, with the

new iteration of the story available on the touchscreen display (Fig. 5-c).

Two researchers (the rst and fourth authors) were involved in the

study, alternating turns during the opening house of the market. They

noted observations and engaged with users to prompt them to ll out the

questionnaires. The study lasted over eight days in two consecutive

weeks (Wednesday to Saturday).

4.2.1. Procedure and tasks

The module was placed near the market’s main entrance and worked

autonomously, i.e., users could walk up to the screen and initiate the

interaction. During the test, we realized that this context demanded

more proactive participation from the researcher. With the installation

being a new element in the market, most users did not feel at ease

initiating interaction. Therefore, the researcher took a more active role

in engaging the passers-by and, especially with older adult users,

assisting during the interaction. This resulted in a collaborative explo-

ration of the visualizations, becoming a bridge for dialogue between the

researcher and the user.

After the initial contact, the researcher explained the nature of the

activity and initiated the story. The intention was for the user to go

through at least two visualizations. Afterwards, the users replied to the

user questionnaire, and the ones who demonstrated more availability

were further interviewed. We also asked users if they agreed to a brief

follow-up interview around seven weeks later.

4.2.2. Methods

We collected data from four different sources:

1. User questionnaire. We conducted three demographics questions

(age, gender, and education level), six questions meant to assess

prior understanding of climate change matters (Table 1 questions 1

to 6), and fourteen questions adapted from the Intrinsic Motivation

Inventory’s (IMI) Interest/Enjoyment (Table 1 questions 7 to 13) and

Value/Usefulness scales (Table 1 questions 14 to 20) (Ryan, 1982;

Ryan et al., 2006). This questionnaire and particular scales were

chosen for their connection with the themes being studied – interest

in the information and enjoyment of its presentation; perceived

usefulness of the action-focused information – and for their format

that was easy and quick to answer (especially in public spaces, we

needed to consider user’s availability). Questions were thematically

adapted to focus on the topics of the study – climate change data

perception –, and were randomly ordered and answered on a scale of

1 – Strongly disagree to 5 – Strongly agree. This study resulted in 64

valid answers.

2. User interview. Afterwards, twelve users answered a semi-

structured interview (I1 to I12), going deeper into the content

interpretation and the user’s perception of how the data was trans-

mitted and interacted with. We asked open questions such as “What

did you think of how the information was presented?”; “Do you think

the information is relevant to your life in particular? Why?”; “How

did the story make you feel about climate change?”; and “Did the

information inspire you to take action?”.

3. Observations. During and after the user’s interaction with the

installation, the researchers took notes on user comments, interac-

tion, apparent engagement, and other relevant points. These notes

were used to inform or contextualise the other results when relevant,

as these observations pointed to spontaneous reactions by users.

4. Follow-up interview. To better understand memorability, what

aspects users felt most compelled by, and possible changes in

perception, we conducted a follow-up user interview of twelve open

questions with eleven users (F1 to F11) six to eight weeks after the

activity. Questions included: “What information most stuck in your

memory?”; “Do you think the experience was different from the

typical way climate change is communicated?”; “Do you think it was

relevant to you personally?”; “Did your perception of climate change

in any way?”; “Do you remember any of the proposals for action?”;

Table 1

Results from the user questionnaire for the Main experimental study – M.E.S. (N

= 64) and the Original Visualizations study – O.V.S. (N = 17). Users replied on a

scale from 1 – Strongly disagree to 5 – Strongly agree.

Questions M.E.

O.V.

1 I am familiar with the topic of climate change. 4.52 4.47

2. I am very concerned about the consequences of climate change.

4.77 4.53

3. I think my individual behavior can make a difference to climate

change. 4.45 4.18

4. I think climate change is created by the media. 1.52 1.24

5. I think solving the issue of climate change is the sole

responsibility of governments. 2.23 2.53

6. I am familiar with natural solutions to climate change (e.g.

mangroves, forests, etc.). 3.33 3.18

7. I really enjoyed learning about whales as a natural solution to

climate change. 4.88 4.41

8. Interacting with this story was fun. 4.77 3.59

9. I thought this story was very pessimistic (R). 1.91 1.70

10. Learning about whales as a natural solution to climate change

did not hold my attention at all (R). 1.77 1.94

11. It was very interesting to learn about whales and climate

change. 4.92 4.59

12. I found this information quite pleasing. 4.86 4.41

13. While interacting with this story, I was thinking that the

information was relevant to me personally. 4.55 3.71

14. I believe this information has some value to me personally.

4.69 4.00

15. I think this activity is useful for learning about what I can do

about climate change. 4.52 3.06

16. I think this information is important because it gives me a

more positive perspective on climate change. 4.50 3.94

17. I would be willing to learn more about what actionsI can take

on climate change because I think it has value for me. 4.75 4.59

18. I think this activity helps me to know what actions I can take

regarding climate change. 4.47 2.82

19. I think doing this activity has made me more pessimistic about

climate change. 2.58 2.18

20. I think this is an important topic to learn more about.

4.86 4.76

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and “Did you change any behavior or did anything differently? Or

are you thinking of doing things differently in the future?”.

4.2.3. Participants demographics

As in the pilot study, we focused the main study on adult users (over

18 years old). The participants (N = 81) were diverse in age: young

adults (aged 18-34): n = 10; adults (aged 35-64): n = 50; senior adults

(aged 65–80+): n = 21. Concerning gender, n = 28 identied as men, n

= 52 as women, and n = 1 their gender identity was not listed. The

implementation context also presented an audience that was diverse in

education level: primary school: n = 9; middle school: n = 9; secondary

school: n = 20; university: n = 43.

4.3. Original visualizations study

Additionally, we saw it as pertinent to understand users’ perceptions

of the original data and its visual presentation in the IMF study (Chami

et al., 2019). Therefore, we performed a parallel in-person study with

seventeen users (O1 to O17), recruited from within the same community

as the main study through word-of-mouth.

We asked users to reply to the same user questionnaire (4.2.2). First,

there are the three demographic questions (age, gender, and education

level) and the ve “prior perceptions on climate change” questions. We

then presented the three visualizations from the original IMF document

through a touch-screen device and asked users to navigate the visuali-

zations at will. Afterwards, we asked users to reply to the remaining

questionnaire with the fourteen IMI-adapted questions. We also con-

ducted semi-structured interviews (4.2.2) to probe further the user’s

perception of the data and visual presentation.

Results for the main study and original IMF visualizations study are

presented in the following section.

5. Results

The answers from the user questionnaire were organised in a table,

and the data was qualitatively analysed following the IMI scale (Ryan,

1982; Ryan et al., 2006). This resulted in a compilation of the average

scores per question and scale. All questions and results for both the main

experimental study and the original visualizations study can be found in

Table 1.

The user interviews, observation notes and follow-up user interviews

were transcribed and then thematically analysed (Braun and Clarke,

2022) by colour coding according to the three aspects of data humanism

we focused on: a) contextualization, b) personalization and c) proposed

actions. This coding led to the organisation of the qualitative data into

thematic clusters that were then linked to the results of the user ques-

tionnaire to understand the impact of the tested communication di-

mensions. The results are presented below, rst examining the users’

prior knowledge and perceptions of climate change, then the overall

results, and then the main analysis regarding data humanism.

5.1. Audiences’ prior perceptions of climate change

The rst part of the questionnaire focused on the users’ prior

knowledge and perceptions of climate change. These led to results

(expressed as a percentage of agreement) that conrmed current

trends (Leiserowitz et al., 2022). Based on the 1 to 5 Likert scale,

users were very familiar with climate change – 92% (Q1), and very

concerned about it – 98% (Q2). People did not believe that climate

change was a media creation – 8% (Q4). Users thought their behavior

could make a difference – 89% (Q3), with only 16% (Q5) thinking

that the government alone should solve the issue “[the solutions]

inspired but I also think that part of this change has to be implemented by

governments.” (I8). A lower 52% (Q6) said to be familiar with natural

solutions to climate change, primarily pointing to forests as the rst

thing that came to mind. Two users (I4, I5) expressed their surprise

and unfamiliarity with the whales as carbon-capturing organisms: “I

had no idea that whales absorbed carbon.” (I4); “I think that there should

be more activities like this because I had no idea of the importance of

whales.” (I5).

The follow-up interviews also point to the efcacy of engaging users

with this less-known subject. All users mentioned some aspect of the

whale information or marine ecosystems as the topics that rst came to

mind from the activity. Five users reference human impact – ocean

waste, noise pollution, or vessels (F1, F2, F3, F5, F9), two mention the

importance of whales in their ecosystem (F6, F8), and four mention

whales as natural solutions for climate change (F4, F7, F10, F11).

The original visualizations study presented similar results for the

questions related to users’ general perception of and concern with

climate change (Q1 to Q6). Likewise, the answers related to the

importance of the information (Q17 and Q20). These results point to

both groups having a similar attitude towards climate change.

5.2. Perceived enjoyment and value of the interactive installation

The overall results regarding Perceived Enjoyment and Value of the

datastory installation were very positive, with participants’ subjec-

tive experience related to Interest/Enjoyment at 4.61 (Q7–13) and

Value/Usefulness at 4.46 (Q14–20). Not surprisingly, the original

IMF visualizations scored less: with 3.48 for enjoyment and 3.62 for

value. The lack of interactivity and dense visual composition of the

IMF visualizations was noted by users: “This is boring. It has a lot of

text. I don’t even know where to look rst.” (O2). The interactive ele-

ments and story cadence of the data-story prototype helped with

engagement and interpretation of the visualizations, being particu-

larly important for communicating complex information and

focusing the user’s attention on certain points: “I have trouble

concentrating and changing information helps me pay attention.” (I8);

“The interactive things, the person absorbs much more.” (F6).

5.3. Data humanism strategy 1: contextualization of the data

5.3.1. Context through the data-story

The whale story was well received, with scores demonstrating that

users immensely enjoyed learning about whales as natural solutions

to climate change – 100% (Q7) and 100% (Q11). We used the whale

story to give context to several data sets. For example, one of the

visualizations in the prototype shows the whale population over

time, becoming almost extinct but slowly recovering since 1986

(Fig. 2– rst screen). Despite showing the “negative” data, we

highlighted “positive” aspects to inuence the data-story. Users

noticed and commented on this particular point: [how they felt after

the story] “Happy to know that whales are recovering ” (P1); “From the

numbers of whales growing, I’m more optimistic” (P11). The follow-up

interviews also mentioned this positive aspect of the data-story: “I

think that little by little, as in the case of whales, it is changing because the

whaling situation has drastically reduced.” (F7); “I remember it showing

some years while the number of whales increased a lot.” (F6). During the

interviews, participants mentioned that since whales as nature-based

solutions are not an obvious fact, the concept is more impacting and

the data is easier to remember: “I got a greater awareness of the

importance that whales have in the ecosystem, and I had no idea.” (F4);

“I had no idea that whales played such an important role.” (F7); “It was

the question of the whales being ecologically a solution, which is some-

thing I was not expecting at all.” (F10).

Another impacting topic was the effect of plastic pollution in the

Ocean. While this is an intensely debated issue already addressed by

legislation in several countries, the story added meaning to the data

by showing the consequences of plastic pollution towards the whale

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characters: “I had no idea that plastic could harm whales so much. That’s

what impressed me the most” (I1); “The reference to micro-plastics was

nothing new, but it was there in a way that was perhaps more explicit and

that stuck in my memory.” (F1).

5.3.2. Context through comparisons to more familiar metrics

The 100% (Q12) score also points to the information being consid-

ered as presented enjoyably. Comparing the data to more familiar

contexts assisted in interpretation: “Often when they talk about

numbers, I don’t know the scale, so relating to things I’m more familiar

with, it’s easier to understand.” (I8); “Having a comparison helped me to

better understand the dimension of the number ” (I9). The comparisons

were also mentioned in the follow-up interviews as a factor that

assisted in understanding the data: “I remember the amount of CO2

that the whales managed to accumulate inside themselves (. . .) compared

to the trees.” (F4); “These are such huge numbers that we are unable to

imagine or have a term of comparison. And I think that the visual com-

parisons (. . .) help a lot.” (F11).

In the original IMF visualizations, questions for interest and enjoy-

ment scored signicantly less – 82% (Q7), 88% (Q11) and 88%

(Q12). User comments point to a disconnection with the data and a

lack of contextualization: “Basically, what is the intention of this? It’s

just so we know: “this is good, it’s already happening”, or this has po-

tential (…)?” (O1); “Show me comparisons. For example, compared to a

car. Having a comparison with our day-to-day life.” (O8); “I couldn’t tell

if it’s positive or negative. The information lacks context.” (O6).

5.4. Data humanism strategy 2: personalizing the data

Results for the questions connected with the personal relevance of

the data point to a lack of connection with the information presented in

the original IMF visualizations – 65% (Q13) and 76% (Q14). In the

interactive data-story, users thought the information was very relevant

to them personally – 95% score (Q13), 98% (Q14). This suggests that the

personalization strategies assisted in connection with the data.

We observed users positively engaging with the interactive elements

of the story that asked them to input personal data to personalise the

data-story visualizations. For example, we noted expressions of sur-

prise when users were asked to input their height and the visualised

data dynamically compared it to the whale’s size (“the whale is X

times your size”). These elements also granted a sense of active

participation in the data-story: “The good part is that I felt I was

participating too, that this was done for us to participate and better retain

the information.” (F2).

During the follow-up interviews, some users recalled the personali-

zation elements as helpful and engaging: “The part where you had to

interact to see the countries where there were more [emissions], (. . .) I

think it ends up making you curious. So when you click, you’re making

comparisons.” (F6); “Since we are entering “personal” data, like age and

height, we are comparing with ourselves. These comparisons helped in

perceiving other numbers that are not so familiar to us on a day-to-day

basis.” (F11).

5.5. Data humanism strategy 3: relating to actionable solutions

5.5.1. Positive climate change messages

Overall the data-story was not considered pessimistic – 14% (Q9) and

23% (Q19). On the other hand, when the question was formulated

positively – if the information gave a more positive perspective on

climate change – the results indicated agreement with an 88% score

(Q16).

The user interviews echo the complexity of the issue, for example,

with users commenting that the story was realistic and not neces-

sarily pessimistic (I7). Participants voiced: “I was a little more opti-

mistic to know that whaling is not done as it used to be, but it also makes

me worried to know that such a drastic change is needed and I don’t see

people doing what is necessary.” (I8). Another user mentioned feeling

“More pessimistic because I had no idea how plastic could harm whales so

much. Plastic, ships. . . ” (I1), but also that the information inspired

them to take action: “Yes. Pick up trash on the beach. Don’t ignore it.

(…) Separate the garbage at home.” (I1). However, it is encouraging

that users commented positively on the differences in the commu-

nication choices of the prototype against mainstream media: “Usually

they [the media] just say the situation is bad, but we don’t know what to

do.” (I11).

The follow-up interviews validated this analysis. Nine interviewees

responded that the experience did not alter their perception of

climate change, with only one changing to a slightly more optimistic

outlook: “Maybe I even got a little more optimistic. Maybe it was Greta’s

fault, and I thought the world would end.” (F9). Another user says: “I’m

sadder because maybe I wasn’t aware of the situation”, but then they

elaborate: “But it’s a good sad in the sense that I know I can also do

something to change.” (F2). Nevertheless, users appreciated how the

data was communicated. They considered it useful: “I still have the

same sense of alertness and responsibility, but I was left with a sense of

greater awareness of the importance that whales have in the ecosystem.”

(F4); “There’s a little light at the end of the tunnel also because the issue

of whales, I had no idea the effect whales could have in contradicting

global warming.” (F7).

5.5.2. A sense of agency by proposing action

The data-story proposals for taking action against climate change

were considered helpful and created a sense of agency in climate

matters. The results reveal that the activity helped teach what ac-

tions users could take, scoring 95% (Q15) and 91% (Q18). The in-

terviews underline these results: “[if they found the information

relevant] Yes as it talks about (…) actions that people can do daily.”

(I6); “There were suggestions I didn’t know and are things I can do at

home in the day-to-day.” (I8). A couple of users (I2, I3) said they didn’t

learn much about solutions because they were already quite

informed on the subject, but the experience helped to reinforce them.

In the follow-up interviews around seven weeks later, ten users (all

except F2) mentioned remembering forms of action that they already

implemented before the experience and, therefore, they already did

what they could: “It helped more in the perception of the problem,

because in the day-to-day what I did I continue to do.” (F3); “I already

had this type of behavior, so I really didn’t change anything.” (F10).

The actions listed were related to recycling (n = 8), plastic (n = 6),

ocean pollution (n = 5), meat consumption (n = 2), and energy use (n

= 1). Noticeably, several other suggestions were not mentioned. Still,

the interaction with the data-story helped reinforce sustainable

habits: “I thought there are things I’m doing well and I should continue to

do, and even improve.” (F1). One user said they were inuenced to

adopt more sustainable behaviors: “If I see garbage, I pick it up. (. . .) I

also started to do more recycling. I avoid eating so much meat.” (F2).

The two questions related to solutions presented the lowest results in

the original visualizations questionnaire – 41% (Q15) and 35%

(Q18). These results reect the lack of connection to actionable

proposals in the IMF visualizations. Six users explicitly commented

on the lack of proposals for action: “I have no idea what I’m supposed

to do.” (O9); “It might be helpful to specify more if there are things we can

do as individuals.” (O1); “And what can I do? Beats me! The information

could link to a set of actions so people know what they can do.” (O7).

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6. Discussion

In this section, we reect on users’ perceptions towards climate

change datasets, and how this is shaped by the way they are commu-

nicated. We analysed the original IMF visualizations and the interactive

data-story, and while we did not set up a direct comparison between the

two, still understanding what did and did not work in both visualizations

can point to promising techniques for engagement with climate data. In

the following, we unpack insights intended to further the debate on the

importance of communication choices and how climate change data

interactions are designed. Instead of a denite generalized strategy, we

aim to deepen the conversation within the design and HCI communities,

fostering research that considers these aspects to better engage diverse

audiences with climate change topics.

6.1. Adding context for more relatable data interactions

As Lupi mentions (G. Lupi, 2017), the data that is included or

excluded denes what story is told through the visualization. By

choosing additional layers of infor-mation to give context to the data, we

successfully inuenced the narrative the data was supporting. Also,

communicating climate change through an unusual topic (whales as

carbon-capturing natural solutions) effectively engaged users with the

data. Furthermore, crafting the data-story around more-than-human

empathy illuminates avenues of including non-anthropocentric voices

in an effective way, as discussed by (Akama et al., 2020; Forlizzi, 2018).

Still, we acknowledge the difculty of representing the

more-than-human (the whale and the ocean system, in our case) through

human interpretation and perception. HCI work should continue to

explore how to give non-human entities a voice and more prominence in

our representations of climate change topics (Mencarini et al., 2023),

also considering climate justice commitments (Doggett et al., 2023).

Rooting the communication activity in storytelling and mundane

contexts such as the local market, brings the topic to a wider variety of

audiences, including some who might not have been previously inter-

ested in topics of sustainability, a challenge discussed by (Paraschivoiu

and Layer-Wagner, 2021). Equity and access, particularly in designed

spaces, represent clear challenges for engagement with scientic data,

with “science capital” — a concept used to assess an individual’s rela-

tionship with science as a consequence of class and other

socio-structural issues — representing a clear faultline (DeWitt and

Archer, 2017) that HCI interventions can assist in addressing.

Responding to recent calls for HCI to support science communication

efforts (Williams et al., 2022), our study takes these concerns from the

digital to the physical realm.

Climate change as an environmental and societal problem is now a

topic that many audiences are somewhat familiar with (Leiserowitz

et al., 2022). However, the scientic data and its specicities are still

primarily abstract to many users. Our study demonstrated that carefully

crafting the data visualizations by relating to the users’ context and

personal details (humanising the data), as called by (U. N. D. of Global

Communications 2022), or creating deeper connections through a form

of “participatory” data (Zhao and Sun, 2022), greatly helped in under-

standing the real meaning of the numbers. Information personalization

strategies are well positioned to contradict the “one-size-ts-all”

approach of many data visualizations (Chapman et al., 2017), and re-

sults suggest that personalization does help in connecting the user with

climate change data. Our research was intended as an initial probe into

applying these approaches within HCI climate change engagement.

Future work should continue to explore these strategies (O’Neill et al.,

2015). Engaging with different audiences within particular commu-

nities, leveraging their own experiences and stories, is a promising

avenue for future design applications. Digital technologies are in a

privileged position to assist in responding to this urgent engagement

need.

6.2. Solutions-oriented visualizations to empower users

Most users felt the data-story helped them learn more about or

reinforce what actions they could take to mitigate climate change, with

proposals feeling personally relevant. Users’ comments demonstrated

the need for linking the data to solutions, highlighting how the story

transmitted hope through action. The follow-up interviews point to the

need to reinforce this solution-oriented communication and ensure that

positive engagement during the activity is translated to longer-term

perception. People remember best the information linking to what

they already knew or did. Future research could focus on furthering

personalization of the proposed actions by analysing what people

already do. Also, the use of participants’ mobile phones could facilitate a

further and longer connection with the data. These strategies should

ideally be tested through longitudinal studies.

Focusing on suggestions for action that the user can easily implement

made the data feel more personal and relatable. However, despite

encouraging more action-focused interactions, this result also highlights

the challenge of engaging non-expert audiences with systemic change.

When designing the datavisualizations and the link to actionable pro-

posals, we considered recent criticism of SHCI regarding a generalised

focus on individual action instead of broader system change (Blevis

et al., 2015; Brynjarsdottir et al., 2012; Forlizzi, 2018; Knowles et al.,

2018; Fritsch et al., 2019). However, the proposals for action were

changed from the pilot to the main study, following user feedback

(Section 4.1.3), shifting from broader social and political action to

personal action. The focus of this study is not on testing possible

behavior change through persuasion, an approach widely used in SHCI

but that has been labelled as narrow and possibly ineffective (Bryn-

jarsdottir et al., 2012), but rather on the importance of message creation

and communication choices in climate change interactions and how

they inuence perception-change of such a negatively charged and

biased issue. Nonetheless, our study touched on the challenge of con-

necting users to actions outside their personal sphere of inuence, and

their perceived role and responsibility within these more complex so-

lutions. Our study connects and extends on related work pointing to

potential avenues for furthering research, like engaging communities

collaboratively (Arag´on et al., 2021) and connecting to ofcial in-

stitutions or environmental organizations (Paraschivoiu and

Layer-Wagner, 2021). These interactions give users a sense of agency

and collaborative satisfaction while linking to broader solutions. The

personalization strategies discussed previously can assist in connecting

particular groups to relevant action within and outside their

communities.

6.3. The challenge of countering the negative framing associated with

climate change

The results from the enquiry about humanized data helping users to

have a more positive outlook on climate change were the most complex

to evaluate. Users did not consider the data-story as pessimistic, nor that

it made them more cynical about climate change. Also, they appreciated

the proposals for action, as discussed in the previous section. Still, few

found the experience “positive” or as giving them an optimistic outlook

on the future.

The framing of how items are presented has an effect on user’s

adoption of sustainable behaviors, as discussed in the HCI application by

(Starke et al., 2021). We build on this principle by testing it in climate

change data presentation. The topic of “climate change” tends to trigger

the existing negative frames already in place. For example, one user

commented that when they realized it was about the impact of the

Anthropocene on marine ecosystems, they expected the story to have a

dramatic ending (P9). People have come to expect negative narratives

associated with climate change, and even with different strategies in

place to try and counter it, this hard-set bias is challenging to contradict

and inevitably takes time and consistent interaction, as discussed by

M. Ferreira et al.

International Journal of Human - Computer Studies 192 (2024) 103341

(Lakoff, 2010). In response to this tendency, initiatives like Good Energy

(Joyner et al., 2022) or Transmedia for Change (T4C) (Pratten, 2015)

urge storytellers to engage audiences through positive messages that

inspire and motivate, in line with the proposals for better climate change

engagement mentioned in 2.1.1. Furthermore, the limited use of these

strategies in previous HCI research (Ferreira et al., 2022) points to op-

portunities for using engaging interaction to communicate climate data

in novel (and less neutral) forms.

Linking the audience’s emotions to climate change scientic infor-

mation has been explored in HCI (Arag´on et al., 2021). Our research

builds on this work by specically exploring how communication stra-

tegies inuence engagement with and emotional perception of the in-

formation. By carefully considering what is transmitted and how we

specically worked to advance strategies to use interactive data hu-

manism to inuence user relations with climate change topics. Our re-

sults point to the importance of not only confronting users with the topic

but actively attempting to link it to personal elements or actionable

proposals (Ferreira et al., 2022). Still, results also underlie the incredible

complexity of communicating climate change and the difculty of

associating positive frames with this topic. The complexity of framing

efcacy and alteration corroborates related work where mixed results

were found in negative (Hornsey and Fielding, 2016; Ettinger et al.,

2021; Bloodhart et al., 2019) versus positive messages (O’Neill and

Nicholson-Cole, 2009; Feinberg et al., 2011; Hart and Feldman, 2016;

Dasandi et al., 2022; Chadwick, 2015). However, recent guidelines such

as (Corner et al., 2015; Chapman et al., 2016; Corner et al., 2018) call for

a shift towards more positive framing focused on action. The comments

made by users point to this need to present more diverse narratives that

don’t focus only on negative consequences.

We discussed encouraging results related to designing more relatable

climate change interactions through data humanism, especially when

focusing on action. We built upon previous research that has started to

use this approach within the HCI research community, looking into

applying it in the untested realm of climate change data visualisations.

However, these strategies must be further tested as shifting negative bias

is extremely challenging. Experimenting with novel ways of evaluating

these activities and forms of assisting in the retention and application of

the information opens exciting prospects for future work.

6.4. Limitations of the study

Engaging users in the evaluation process in the wild, during the time

devoted to their daily routines (i.e. shopping at the local market), or

allocated to specic actions (i.e. visiting a museum or a specic location)

echos HCI challenges reported in research (Silva et al., 2017; Houben

et al., 2019). Therefore, the testing protocols had to adapt to these

particularities. Findings are limited to the degree of analysis used.

Additionally, the open nature of the design process signies a

multitude of options within each creative step. The artefact presented in

this paper is but one example of application, even if applying different

strategies for more accurate results. Nevertheless, research artefacts are

useful even if they result from a subjective process (Hengeveld et al.,

2016).

Lastly, the studies’ duration was not extensive enough to determine if

the experience could inuence long-term perception or habit changes.

This aspect was tentatively addressed in the follow-up interviews some

weeks after the experience. Still, a longitudinal study would give

meaningful insights into the effectiveness of the communication stra-

tegies tested.

6.5. Future directions

Besides the implications derived from the exploration of each

research enquiry discussed previously, in this section we compile a set of

future directions informed by the work.

Considering one of the current limitations identied, conducting

long-term studies to assess further the effects of the experience on user

perception and habit changes would be extremely useful. Furthermore,

engaging audiences in different cultural and social contexts is a stimu-

lating avenue for data humanism interactions moving forward, as these

would explore the strategies’ potential to link datasets to diverse audi-

ences. These explorations could also consider closer links to commu-

nities and personal values – again, exploring the intrinsic potential of

data humanism in connecting groups and individuals with data through

their particular experiences and concerns. Additionally, alternative

features within the data humanism framework and diverse datasets must

be explored. As research and academic knowledge in this eld evolve,

it’s important to update and rene the list of design insights

continuously.

When looking at the results from the study and the challenges related

to climate change, it is crucial to keep exploring engaging ways of

connecting lay audiences with system change. The HCI community has

pointed to this gap in recent years. Engaging interventions to connect

complex systemic change to individual citizens and communities,

making it relevant and achievable, is crucial. In addition, continuing to

explore alternative ways to represent the more-than-human opens

stimulating possibilities for HCI and design research. For example, the

potential of Large Language Models to assist in representing different

perspectives of other species is a path with great creative and conceptual

potential. These explorations also demand careful debate and consid-

eration of their limitations.

7. Conclusion

HCI and design practitioners are in a privileged position to assist in

the evolution of socially responsible messages in an informative but also

engaging and action-focused manner. We set out to investigate data

humanism applied to climate change communication, focusing on sto-

rytelling, personalization, contextualization, and connection to action-

able solutions. Through a research through design study, we intended to

probe if and how the strategies used assisted in fostering positive and

empowering interactions with climate change data. For this purpose, we

conducted several studies: an evaluation of the original data visualiza-

tions from the study that informed our prototype, and two studies of our

interactive data-story in two contexts – a science museum and a local

food market. We used mixed methods to investigate: a) If and how users

feel connected to the humanized data; b) If the humanized data affords

users a positive outlook on climate change; c) If solutions-oriented vi-

sualizations create a feeling of empowerment and agency towards

climate matters. Finally, we circled back to eleven participants around

seven weeks later to probe memorability, what aspects users felt most

compelled by, and possible changes in perception.

The data humanism approach challenges a sector of data visualiza-

tion that focuses on neutrality and simplicity for effective data

communication (Zhao and Sun, 2022; Tufte, 2013; Cairo, 2016) leaning

towards an observer-dependant, more complex and nuanced approach

(Drucker, 2011) in an attempt of reconnecting audiences with climate

change data. Our results suggest that adding layers of information to

contextualize the data helps engage and connect with climate change

data and that solutions-oriented visualizations effectively engage users

and create or reinforce a feeling of agency in climate matters. However,

even though users appreciate the focus on action, the tested interactions

with humanized data were insufcient to alter the person’s perception of

the issue considerably.

In summary, the insights and discussion generated from the study

illuminate the potential of combining data humanism with HCI in-

terventions. This paper intends to deepen the debate surrounding the

complexity of engaging diverse audiences with climate change data and

building on the challenges of shifting the climate change dialogue from

one focused on “doom and gloom” to action-focused narratives. In this

context, designing data visualizations that are relatable and focused on

solutions might be as important as accuracy. These inquiries underlie the

M. Ferreira et al.

International Journal of Human - Computer Studies 192 (2024) 103341

ever-growing role that interactive experiences can and should play in

these crucial communication challenges.

CRediT authorship contribution statement

Marta Ferreira: Writing – original draft. Nuno Nunes: Writing –

review & editing. Pedro Ferreira: Data curation. Henrique Pereira:

Data curation. Valentina Nisi: Writing – review & editing.

Declaration of competing interest

The authors declare the following nancial interests/personal re-

lationships which may be considered as potential competing interests:

Marta Ferreira reports nancial support was provided by Fundaç

ao para

a Ci

encia e a Tecnologia and European Union’s Horizon Europe

Framework Programme under grant agreement 101,094,036, project

LoGa Culture.

Data availability

The data that has been used is condential.

Acknowledgements

Research funded by Fundaç

ao para a Ci

encia e a Tecnologia (FCT)

through a PhD research grant – SFRH/BD/144434/2019, and the Eu-

ropean Union’s Horizon Europe Framework Programme under grant

agreement 101094036, project LoGa Culture.

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